Climate change vulnerability assessment of forests in the Southwest USA

Thorne, James H.; Choe, Hyeyeong; Stine, Peter; Chambers, Jeanne C.; Holguin, Andrew; Kerr, Amber; Schwartz, Mark W.

doi:10.1007/s10584-017-2010-4

Cited by 66 publications

(55 citation statements)

References 48 publications

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“…Previous studies have indicated a high level of climate change exposure in the foothills of CA (Thorne et al, 2017(Thorne et al, , 2018 2015). Other dynamic vegetation model simulations indicate contracting needle leaf evergreen forest cover in some areas we identify as having low drought vulnerability (Jiang et al, 2013).…”

Section: Discussionmentioning

confidence: 98%

Near‐future forest vulnerability to drought and fire varies across the western United States

Buotte

Levis²,

Law

et al. 2018

Global Change Biology

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Recent prolonged droughts and catastrophic wildfires in the western United States have raised concerns about the potential for forest mortality to impact forest structure, forest ecosystem services, and the economic vitality of communities in the coming decades. We used the Community Land Model (CLM) to determine forest vulnerability to mortality from drought and fire by the year 2049. We modified CLM to represent 13 major forest types in the western United States and ran simulations at a 4‐km grid resolution, driven with climate projections from two general circulation models under one emissions scenario (RCP 8.5). We developed metrics of vulnerability to short‐term extreme and prolonged drought based on annual allocation to stem growth and net primary productivity. We calculated fire vulnerability based on changes in simulated future area burned relative to historical area burned. Simulated historical drought vulnerability was medium to high in areas with observations of recent drought‐related mortality. Comparisons of observed and simulated historical area burned indicate simulated future fire vulnerability could be underestimated by 3% in the Sierra Nevada and overestimated by 3% in the Rocky Mountains. Projections show that water‐limited forests in the Rocky Mountains, Southwest, and Great Basin regions will be the most vulnerable to future drought‐related mortality, and vulnerability to future fire will be highest in the Sierra Nevada and portions of the Rocky Mountains. High carbon‐density forests in the Pacific coast and western Cascades regions are projected to be the least vulnerable to either drought or fire. Importantly, differences in climate projections lead to only 1% of the domain with conflicting low and high vulnerability to fire and no area with conflicting drought vulnerability. Our drought vulnerability metrics could be incorporated as probabilistic mortality rates in earth system models, enabling more robust estimates of the feedbacks between the land and atmosphere over the 21st century.

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Section: Discussionmentioning

confidence: 98%

Near‐future forest vulnerability to drought and fire varies across the western United States

Buotte

Levis²,

Law

et al. 2018

Global Change Biology

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“…, Thorne et al. ). This is particularly the case in the Southwest where several major temperate ecosystem types find their southernmost limits in North America (Brown et al.…”

Section: Introductionmentioning

confidence: 99%

“…), or have relatively coarse thematic or spatial outputs (>1:1,000,000 map scale) that are useful for broad policy and strategy but may be too general for subregional applications (Thorne et al. ). For these reasons, we chose an approach that would generate a regional assessment of increased spatial and thematic detail to convey vulnerability to future climate.…”

Section: Introductionmentioning

confidence: 99%

“…Climate-related effects to vegetation patterns will likely stem from an increase in summer temperatures, increase in frost-free days, reduced snow accumulation and incidence of albedo, and other related indicators (Thomey et al 2011, Williams et al 2013. The continuing alteration of landscapes coupled with clear indications of a changing climate has signaled an urgency among managers to determine probable future outcomes and options for climate adaptation (Friggens et al 2013, Williams et al 2013, Thorne et al 2017. This is particularly the case in the Southwest where several major temperate ecosystem types find their southernmost limits in North America (Brown et al 1998) and hence would be expected to be particularly sensitive to a warming climate (Boisvert-Marsh et al 2014).…”

Section: Introductionmentioning

confidence: 99%

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Using climate projections to assess ecosystem vulnerability at scales relevant to managers

2019

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Land managers require information about the ongoing and potential effects of future climate to coordinate responses for ecosystems, species, and human communities at scales that are operationally meaningful. Our study focused on the vulnerability for all upland ecosystem types of Arizona and New Mexico in the southwestern United States. Local vulnerability across the two‐state area was represented by the level of departure for late 21st‐century climate from the characteristic pre‐1990 climate envelope of the ecosystem type at each given location, resulting in a probability surface of climate impacts for the two‐state area and an uncertainty assessment based on agreement in results among multiple global climate models. Though the results varied from one ecosystem type to the next, the majority of lands were forecast as high vulnerability and low uncertainty, reflecting significant agreement among climate model projections for the southwestern United States. We then tested our results in relation to ongoing ecological processes that have both regional and global change implications and discovered significant relationships with wildfire severity, upward tree species recruitment, and the encroachment of scrub into semidesert grassland. The testing helped determine the efficacy of the vulnerability surface, as a product of relatively high spatial and thematic resolution, in supporting local planning and management decisions. Most important, this study links climate and changes in vegetation by ecosystem processes that are already ongoing. The results affirm the value of climate model downscaling and show that this portable approach to correlative modeling has value in determining the location and magnitude of potential climate‐related impacts.

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“…The CEA approach integrates the distribution of a vegetation type, typically derived from remote sensing, with mapped current climate and projected future climate conditions to determine the climate envelope of that type and assesses the level of climate change for each pixel of that type under future conditions (Thorne, Boynton, Holguin, Stewart, & Bjorkman, 2016;Thorne, Choe, Boynton, et al, 2017;Thorne, Choe, Stine, et al, 2017). CEA differs from climate impact approaches that predict potential range or movement, such as species distribution models, in that CEA is an in situ approach that predicts the climatic shifts within a set area between time periods; it does not predict where species will shift in order to maintain an optimal climate envelope (e.g., Phillips, Anderson, & Schapire, 2006;Thorne et al, 2013), nor does it predict where or how fast a given set of climatic conditions will move (i.e., climate change velocity; Ackerly et al, 2010;Dobrowski & Parks, 2016).…”

Section: Introductionmentioning

confidence: 99%

Climate risk on two vegetation axes—Tropical wet‐to‐dry and temperate arid‐to‐moist forests

Williams

Rivera

Choe

et al. 2018

Journal of Biogeography

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Aim Assess climatic risk to vegetation types associated with tropical and temperate ecosystems based on exposure analysis, which models future risk as a function of deviation from current climate variable distributions. Location Oaxaca State, Mexico. Taxon Broadly defined vegetation types used in state‐ and national‐level vegetation classification systems. These types can be grouped into series representing dry‐to‐wet conditions for tropical and temperate vegetation. Methods We used climate exposure analysis to compare current and future climate parameters for the major vegetation types of Oaxaca. This technique integrates a recent vegetation map with historical climate data (1981–2010) to produce a baseline climate layer that is compared to climate projections made with five different global circulation models for near‐future (2015–2039) and end‐century (2075–2099) periods using two emissions scenarios (RCP 4.5 and 8.5). We classified the frequency distribution of the baseline climate into five exposure classes where the closer values are to mean climate conditions, the lower the exposure. Future exposure was estimated by classifying the vegetation pixels into the same exposure classes, now based on future climate values. Increased exposure risk was assessed based on the fraction of pixels that moved into higher exposure classes from one period to another. Results and main conclusions Our analysis showed four general trends: (a) the higher, current track emissions scenario produced much larger end‐century climate exposure; (b) for the tropical vegetation series, tropical evergreen forests are projected as most exposed by end‐century; (c) for the temperate vegetation series the matorral‐shrubland and conifer forests are the most impacted; and (d) the five GCMs considered showed some convergence in their end‐century climate exposure predictions, with coastal and low‐elevation areas of the State projected to experience the greatest exposure, and the interior mountain slopes and central region projected to experience the least exposure and be the most climatically stable.

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Climate change vulnerability assessment of forests in the Southwest USA

Cited by 66 publications

References 48 publications

Near‐future forest vulnerability to drought and fire varies across the western United States

Near‐future forest vulnerability to drought and fire varies across the western United States

Using climate projections to assess ecosystem vulnerability at scales relevant to managers

Climate risk on two vegetation axes—Tropical wet‐to‐dry and temperate arid‐to‐moist forests

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